#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 Joseph Helm and Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Data;
using HeuristicLab.Common;
using HeuristicLab.Encodings.PackingEncoding;
namespace HeuristicLab.Problems.BinPacking {
[Item("Packing-Ratio Regular Identical-Bin Evaluator", "Represents an evaluation-algorithm for regular-shaped bin-packing problems with identical bins which calculates the ratio between packed and unpacked space. Found in Falkenauer:1996")]
[StorableClass]
public abstract class PackingRatioRegularIdenticalBinEvaluator : RegularSimpleRotationIdenticalBinPackingPlanEvaluator
where D : class, IPackingPosition
where B : PackingShape
where I : PackingShape, IPackingItem {
[StorableConstructor]
protected PackingRatioRegularIdenticalBinEvaluator(bool deserializing) : base(deserializing) { }
protected PackingRatioRegularIdenticalBinEvaluator(PackingRatioRegularIdenticalBinEvaluator original, Cloner cloner)
: base(original, cloner) {
}
public PackingRatioRegularIdenticalBinEvaluator() : base() { }
protected override DoubleValue Evaluate() {
DoubleValue quality = new DoubleValue(0);
IPackingPlan plan = PackingPlanParameter.ActualValue;
B binMeasure = PackingBinMeasuresParameter.ActualValue;
ItemList itemMeasures = PackingItemMeasuresParameter.ActualValue;
//Check if data is valid
//if (plan.PackingItemPositions.Count != itemMeasures.Count)
// throw new Exception("ERROR: ItemMeasures.count does not match packingPosition.count");
////Check if any items are overlapping or not contained in their bins
//bool itemPositionsAreValid = !HasOverlappingOrNotContainedItems(plan.PackingItemPositions, binMeasure, itemMeasures, nrOfBins);
//if (itemPositionsAreValid)
return CalculatePackingRatio(plan as PackingPlan);
//return quality;
}
/*
Falkenauer:1996 - A Hybrid Grouping Genetic Algorithm for Bin Packing
fBPP = (SUM[i=1..N](Fi / C)^k)/N
N.......the number of bins used in the solution,
Fi......the sum of sizes of the items in the bin i (the fill of the bin),
C.......the bin capacity and
k.......a constant, k>1.
*/
public static DoubleValue CalculatePackingRatio(PackingPlan plan) {
int nrOfBins = plan.NrOfBins;
double result = 0;
//C
//double usableSpace = binMeasure.MultipliedMeasures;
//nrOfBins = N
for (int i = 0; i < nrOfBins; i++) {
//C
//double usableSpace = plan.GetPackingBinMeasuresForBinNr(0).MultipliedMeasures;//plan.GetPackingBinMeasuresForBinNr(i).MultipliedMeasures;
//var indexes = plan.PackingItemPositions.Select((Value, Index) => new { Value, Index }).Where(s => s.Value.Value.AssignedBin == i).Select(s => s.Index);
//var packedItemsInThisBin = plan.PackingItemMeasures.Select((Value, Index) => new { Value, Index }).Where(s => indexes.Contains(s.Index));
//Fi
//double usedSpaceInThisBin = packedItemsInThisBin.Select(s => s.Value.MultipliedMeasures).Sum();
//k = 2 --> (Fi/C)*(Fi/C)
//result += (((usedSpaceInThisBin) / (usableSpace)) * ((usedSpaceInThisBin) / (usableSpace))) / (i*i + 1);
var PD = plan.BinPackings[i].PackingDensity;
result += (PD * PD) / (i + 1);
}
result = result / nrOfBins;
return new DoubleValue(result);
}
}
}